Returns a 1-d array of gvar.GVars y[i] constructed from the 1-d array
+of mean values ymean and the 2-d covariance matrix ycov. The
+y[i] are correlated with the primary gvar.GVars in 1-d array x.
+The x-y covariance matrix is xycov whose shape
+is x.shape+y.shape. Note that this changes the gvar.GVars
+in x (because they are correlated with the y[i]); it
+has no effect on the variance or on correlations between
+different x[i]s.
+
+
The following function is useful for constructing new functions that
@@ -1818,29 +1831,29 @@
Number of independent degrees of freedom left after the
SVD cut. This is the same as the number initially unless
svdcut<0 in which case it may be smaller.
Logarithm of the determinant of the covariance matrix after SVD
cuts are applied (excluding any omitted modes when
svdcut<0 and any diagonal zero modes).
diff --git a/doc/html/searchindex.js b/doc/html/searchindex.js
index 7d0bb22..9e2a560 100644
--- a/doc/html/searchindex.js
+++ b/doc/html/searchindex.js
@@ -1 +1 @@
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